diff --git a/Cargo.toml b/Cargo.toml
index b9cc8de..9d7ce23 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -1,7 +1,7 @@
 [package]
 name = "big_o"
-description = "Infers asymptotic computational complexity."
-version = "0.1.0"
+description = "Infers asymptotic computational complexity"
+version = "0.1.1"
 edition = "2021"
 authors = ["Maksym Arutyunyan"]
 repository = "https://github.com/maksym-arutyunyan/big_o"
diff --git a/README.md b/README.md
index 6a226e2..1857968 100644
--- a/README.md
+++ b/README.md
@@ -4,16 +4,18 @@ Infers asymptotic computational complexity.
 
 `big_o` helps to estimate computational complexity of algorithms by inspecting measurement data (eg. execution time, memory consumption, etc). Users are expected to provide measurement data, `big_o` will try to fit a set of complexity models and return the best fit.
 
-## Examples
+## Example
+
+```rust
+use assert_approx_eq::assert_approx_eq;
 
-```rs
 // f(x) = gain * x ^ 2 + offset
 let data = vec![(1., 1.), (2., 4.), (3., 9.), (4., 16.)];
 
-let (best, _all) = big_o::infer_complexity(data).unwrap();
+let (complexity, _all) = big_o::infer_complexity(data).unwrap();
 
-assert_eq!(best.name, big_o::Name::Quadratic);
-assert_eq!(best.notation, "O(n^2)");
-assert_approx_eq::assert_approx_eq!(best.params.gain.unwrap(), 1.0, 1e-6);
-assert_approx_eq::assert_approx_eq!(best.params.offset.unwrap(), 0.0, 1e-6);
+assert_eq!(complexity.name, big_o::Name::Quadratic);
+assert_eq!(complexity.notation, "O(n^2)");
+assert_approx_eq!(complexity.params.gain.unwrap(), 1.0, 1e-6);
+assert_approx_eq!(complexity.params.offset.unwrap(), 0.0, 1e-6);
 ```
diff --git a/src/lib.rs b/src/lib.rs
index b12dac5..2c94a79 100644
--- a/src/lib.rs
+++ b/src/lib.rs
@@ -3,6 +3,20 @@
 //! `big_o` helps to estimate computational complexity of algorithms by inspecting measurement data
 //! (eg. execution time, memory consumption, etc). Users are expected to provide measurement data,
 //! `big_o` will try to fit a set of complexity models and return the best fit.
+//!
+//! # Example
+//! ```
+//! # use assert_approx_eq::assert_approx_eq;
+//! // f(x) = gain * x ^ 2 + offset
+//! let data = vec![(1., 1.), (2., 4.), (3., 9.), (4., 16.)];
+//!
+//! let (complexity, _all) = big_o::infer_complexity(data).unwrap();
+//!
+//! assert_eq!(complexity.name, big_o::Name::Quadratic);
+//! assert_eq!(complexity.notation, "O(n^2)");
+//! assert_approx_eq!(complexity.params.gain.unwrap(), 1.0, 1e-6);
+//! assert_approx_eq!(complexity.params.offset.unwrap(), 0.0, 1e-6);
+//! ```
 
 mod complexity;
 mod linalg;
@@ -18,28 +32,29 @@ pub use crate::params::Params;
 ///
 /// # Example
 /// ```
+/// # use assert_approx_eq::assert_approx_eq;
 /// // f(x) = gain * x ^ 2 + offset
 /// let data = vec![(1., 1.), (2., 4.), (3., 9.), (4., 16.)];
 ///
-/// let (best, _all) = big_o::infer_complexity(data).unwrap();
+/// let (complexity, _all) = big_o::infer_complexity(data).unwrap();
 ///
-/// assert_eq!(best.name, big_o::Name::Quadratic);
-/// assert_eq!(best.notation, "O(n^2)");
-/// assert_approx_eq::assert_approx_eq!(best.params.gain.unwrap(), 1.0, 1e-6);
-/// assert_approx_eq::assert_approx_eq!(best.params.offset.unwrap(), 0.0, 1e-6);
+/// assert_eq!(complexity.name, big_o::Name::Quadratic);
+/// assert_eq!(complexity.notation, "O(n^2)");
+/// assert_approx_eq!(complexity.params.gain.unwrap(), 1.0, 1e-6);
+/// assert_approx_eq!(complexity.params.offset.unwrap(), 0.0, 1e-6);
 /// ```
 pub fn infer_complexity(
     data: Vec<(f64, f64)>,
 ) -> Result<(Complexity, Vec<Complexity>), &'static str> {
-    let mut fitted: Vec<Complexity> = Vec::new();
+    let mut all_fitted: Vec<Complexity> = Vec::new();
     for name in name::all_names() {
         let complexity = complexity::fit(name, data.clone())?;
         if validate::is_valid(&complexity) {
-            fitted.push(complexity);
+            all_fitted.push(complexity);
         }
     }
-    fitted.sort_by(|a, b| a.params.residuals.partial_cmp(&b.params.residuals).unwrap());
-    let best = fitted[0].clone();
+    all_fitted.sort_by(|a, b| a.params.residuals.partial_cmp(&b.params.residuals).unwrap());
+    let best_complexity = all_fitted[0].clone();
 
-    Ok((best, fitted))
+    Ok((best_complexity, all_fitted))
 }
diff --git a/tests/execution_time.rs b/tests/execution_time.rs
index 3440895..aff1b61 100644
--- a/tests/execution_time.rs
+++ b/tests/execution_time.rs
@@ -1,11 +1,12 @@
 use std::time::Instant;
 use std::{thread, time};
+use std::fmt::Write as _; // import without risk of name clashing
 
 #[allow(dead_code)]
 fn write_csv(data: &Vec<(f64, f64)>, path: &str) {
     let mut text = String::new();
     for (x, y) in data {
-        text.push_str(&format!("{},{}\n", *x, *y));
+        let _ = writeln!(text, "{},{}", *x, *y);
     }
     std::fs::write(path, text).expect("Unable to write file");
 }